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Stanford University · on Coursera

Algorithms Specialization

4.9(22,000) on Coursera·380K enrolled
Intermediate 200 hours English Specialization
SkillsAlgorithmsData structuresGraph algorithmsDynamic programmingGreedy algorithmsBig-O analysis

Is this course right for you?

Our take
A rigorous, university-level grounding in algorithms, and about as good as online algorithms teaching gets. It is free to audit.

Good for: programmers who want a serious grounding in algorithms, including for interviews.

Skip if: you are new to programming, or you want a quick interview-prep crammer.

Tim Roughgarden takes four courses from sorting and divide-and-conquer through graph algorithms, greedy methods, dynamic programming and NP-completeness, with real mathematical analysis — proving correctness and deriving complexity, not just memorising patterns. It is language-agnostic, so you implement the ideas in whatever you like.

It is demanding and theory-first, so it is not a quick interview crammer and not for someone new to programming — start with a first programming course instead if that is you. The certificate needs a subscription; the free audit covers the learning. The material is foundational and still relevant.

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About this course

Tim Roughgarden's Algorithms Specialization is among the most respected algorithms courses online — four courses moving from sorting and divide-and-conquer through graph algorithms (Dijkstra, BFS/DFS, SCCs), greedy algorithms, dynamic programming, and NP-completeness. Roughgarden's teaching is exceptional: rigorous mathematical analysis combined with genuine enthusiasm for the subject.

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Instructor

TR
Tim Roughgarden
Coursera instructor
380K+ learners4 courses4.9 instructor rating

Taught by Tim Roughgarden, Professor of Computer Science at Columbia University and formerly Stanford, a leading algorithms researcher.

Frequently asked questions

None in particular, which is unusual and deliberate. Tim Roughgarden teaches the algorithms conceptually and lets you implement the programming assignments in whatever language you prefer — the graders check your answer, not your code style. That said, you do need to already program competently in something, because you will be coding the algorithms yourself rather than following along line by line.

At least a little programming experience and comfort with basic data structures like arrays, linked lists, stacks, and queues. Some mathematical maturity helps too, since Roughgarden includes correctness proofs and running-time analysis. It is billed as an introduction to algorithms, but that means introductory for people who can already code, not for absolute beginners to programming.

It builds the deep understanding that separates people who can reason about algorithms from those who have only memorised patterns, which genuinely helps in interviews. But it is not a LeetCode-style drill course — it is light on the sheer volume of practice problems interviews reward. Pair it with dedicated problem practice; this gives you the why, the grinding gives you the speed.

Genuinely challenging. It is a rigorous, university-level treatment across four courses — divide and conquer, graph algorithms, greedy and dynamic programming, and NP-complete problems — with real proofs and analysis rather than surface tours. People with a maths or CS background cope well; others can absolutely finish it, but should expect to rewatch lectures and wrestle with the harder assignments rather than breeze through.

Yes. You can audit all four courses on Coursera and watch every lecture at no cost, which for a course this conceptual is most of the value. The graded programming assignments and the certificate need a subscription, though financial aid is available if you apply and explain your situation.

The four courses together are a substantial commitment — realistically a few months at a steady weekly pace, more if the maths is new to you. Because each course builds on the last, it rewards doing them in order and actually completing the assignments rather than passively watching, which is where the time genuinely goes.
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